Research Scientist Intern, Data for Embodied AI

The role 

We’re looking for a curious and motivated Intern to join our Science team in London, contributing to the development of large-scale data systems and pipelines that power multimodal foundation models for autonomous driving.

You’ll collaborate closely with experienced ML engineers and researchers to build tools and infrastructure that transform raw real-world data into high-quality training datasets. This role offers the opportunity to work on petabyte-scale video, lidar, and telemetry data—contributing directly to the systems that enable self-learning AI models.

The ideal candidate has a strong foundation in machine learning, data systems, or computer vision, and a passion for scaling AI through high-quality, diverse data. You’ll gain hands-on experience with end-to-end data workflows, experimental design, and data-centric AI research.

What you will bring to Wayve

Essential:

• Currently pursuing a PhD or Master’s degree in Computer Science, Data Engineering, Machine Learning, Robotics, or a related field.
• Strong programming skills in Python, and experience with libraries such as PyTorch, NumPy, and Pandas.
• Understanding of large-scale data processing concepts — e.g. distributed pipelines, batching, data ingestion, or caching strategies.
• Interest in data-centric ML, dataset quality, and understanding how data impacts model performance.
• Familiarity with at least one of: computer vision, sensor fusion, spatio-temporal learning, or foundation model training.
• Motivation to collaborate in an interdisciplinary team and take ideas from prototype to robust, scalable systems.

Desirable:

• Experience working with large multimodal datasets (e.g. video, LiDAR, or other sensor data).
• Familiarity with data orchestration or workflow tools.
• Exposure to distributed computing frameworks like Ray, Spark, or Dask.
• Interest in embodied AI, simulation, or generative data pipelines.
• Track record of scientific contributions through publications at venues such as CVPR, ICCV, CoRL, NeurIPS, ICML, ICRA, RSS, AAAI.
• Experience in bridging research and applied engineering, particularly within robotics or autonomous systems. 

What we offer:

• The chance to work on transformative AI systems with real-world impact on mobility, safety, and autonomy.
• Mentorship from leading ML engineers and researchers working on foundation models and data systems.
• Access to massive multimodal datasets, cutting-edge infrastructure, and high-performance compute.
• A collaborative, respectful, and learning-driven environment that encourages bold ideas and experimentation.
• Potential to contribute to publications or open research efforts at top-tier conferences.